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#llama3 ์ถœ์‹œ๐Ÿ”ฅ ๋กœ์ปฌ์—์„œ Llama3-8B ๋ชจ๋ธ ๋Œ๋ ค๋ณด๊ธฐ๐Ÿ‘€

2 min read 6 months ago
Published on Apr 22, 2024 This response is partially generated with the help of AI. It may contain inaccuracies.

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Tutorial: Exploring the Llama3-8B Model Locally

Video Title: #llama3 ์ถœ์‹œ๐Ÿ”ฅ ๋กœ์ปฌ์—์„œ Llama3-8B ๋ชจ๋ธ ๋Œ๋ ค๋ณด๊ธฐ๐Ÿ‘€

Channel: ํ…Œ๋””๋…ธํŠธ TeddyNote

Overview:

In this tutorial, we will guide you through the process of running and exploring the Llama3-8B model locally. The video showcases how to use the model effectively and provides valuable insights into its capabilities.

Steps to Follow:

  1. Access the Resources:

    • Access the manual for the Llama3-8B model here.
    • Find the code repository on GitHub here.
    • Explore the free e-book tutorial on LangChain here.
    • Visit the LangChain Korean tutorial code repository on GitHub here.

  2. Preparation:

    • Make sure you have Python installed on your local machine.
    • Install the necessary libraries and dependencies as mentioned in the manual or code repository.

  3. Run the Llama3-8B Model:

    • Clone or download the Llama3-8B model code from the GitHub repository.
    • Follow the instructions provided in the manual to set up the model locally.
    • Run the code and explore the functionalities of the Llama3-8B model.

  4. Further Learning:

    • Explore the LLM project on llm.teddynote.com for additional resources.
    • Stay updated on tutorials and projects by following the TeddyNote channel.

  5. Engage and Learn:

    • Participate in the LangChain + ChatGPT + Streamlit course by pre-registering here for notifications and discounts.

Conclusion:

By following these steps, you can successfully run and explore the Llama3-8B model locally. Utilize the provided resources to enhance your understanding of the model and stay informed about upcoming tutorials and projects in the field of language processing.

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